Micro-Anatomical Quantitative Imaging Towards Enabling Automated Diagnosis of Thick Tissues at the Point of Care

Histopathology is the clinical standard for tissue diagnosis. However, histopathology has several limitations including that it requires tissue processing, which can take 30 minutes or more, and requires a highly trained pathologist to diagnose the tissue. Additionally, the diagnosis is qualitative, and the lack of quantitation leads to possible observer-specific diagnosis. Taken together, it is difficult to diagnose tissue at the point of care using histopathology.

Several clinical situations could benefit from more rapid and automated histological processing, which could reduce the time and the number of steps required between obtaining a fresh tissue specimen and rendering a diagnosis. For example, there is need for rapid detection of residual cancer on the surface of tumor resection specimens during excisional surgeries, which is known as intraoperative tumor margin assessment. Additionally, rapid assessment of biopsy specimens at the point-of-care could enable clinicians to confirm that a suspicious lesion is successfully sampled, thus preventing an unnecessary repeat biopsy procedure. Rapid and low cost histological processing could also be potentially useful in settings lacking the human resources and equipment necessary to perform standard histologic assessment. Lastly, automated interpretation of tissue samples could potentially reduce inter-observer error, particularly in the diagnosis of borderline lesions.

To address these needs, high quality microscopic images of the tissue must be obtained in rapid timeframes, in order for a pathologic assessment to be useful for guiding the intervention. Optical microscopy is a powerful technique to obtain high-resolution images of tissue morphology in real-time at the point of care, without the need for tissue processing. In particular, a number of groups have combined fluorescence microscopy with vital fluorescent stains to visualize micro-anatomical features of thick (i.e. unsectioned or unprocessed) tissue. However, robust methods for segmentation and quantitative analysis of heterogeneous images are essential to enable automated diagnosis. Thus, the goal of this work was to obtain high resolution imaging of tissue morphology through employing fluorescence microscopy and vital fluorescent stains and to develop a quantitative strategy to segment and quantify tissue features in heterogeneous images, such as nuclei and the surrounding stroma, which will enable automated diagnosis of thick tissues.

To achieve these goals, three specific aims were proposed. The first aim was to develop an image processing method that can differentiate nuclei from background tissue heterogeneity and enable automated diagnosis of thick tissue at the point of care. A computational technique called sparse component analysis (SCA) was adapted to isolate features of interest, such as nuclei, from the background. SCA has been used previously in the image processing community for image compression, enhancement, and restoration, but has never been applied to separate distinct tissue types in a heterogeneous image. In combination with a high resolution fluorescence microendoscope (HRME) and a contrast agent acriflavine, the utility of this technique was demonstrated through imaging preclinical sarcoma tumor margins. Acriflavine localizes to the nuclei of cells where it reversibly associates with RNA and DNA. Additionally, acriflavine shows some affinity for collagen and muscle. SCA was adapted to isolate acriflavine positive features or APFs (which correspond to RNA and DNA) from background tissue heterogeneity. The circle transform (CT) was applied to the SCA output to quantify the size and density of overlapping APFs. The sensitivity of the SCA+CT approach to variations in APF size, density and background heterogeneity was demonstrated through simulations. Specifically, SCA+CT achieved the lowest errors for higher contrast ratios and larger APF sizes. When applied to tissue images of excised sarcoma margins, SCA+CT correctly isolated APFs and showed consistently increased density in tumor and tumor + muscle images compared to images containing muscle. Next, variables were quantified from images of resected primary sarcomas and used to optimize a multivariate model. The sensitivity and specificity for differentiating positive from negative ex vivo resected tumor margins was 82% and 75%. The utility of this approach was further tested by imaging the in vivo tumor cavities from 34 mice after resection of a sarcoma with local recurrence as a bench mark. When applied prospectively to images from the tumor cavity, the sensitivity and specificity for differentiating local recurrence was 78% and 82%. The results indicate that SCA+CT can accurately delineate APFs in heterogeneous tissue, which is essential to enable automated and rapid surveillance of tissue pathology.

Two primary challenges were identified in the work in aim 1. First, while SCA can be used to isolate features, such as APFs, from heterogeneous images, its performance is limited by the contrast between APFs and the background. Second, while it is feasible to create mosaics by scanning a sarcoma tumor bed in a mouse, which is on the order of 3-7 mm in any one dimension, it is not feasible to evaluate an entire human surgical margin. Thus, improvements to the microscopic imaging system were made to (1) improve image contrast through rejecting out-of-focus background fluorescence and to (2) increase the field of view (FOV) while maintaining the sub-cellular resolution needed for delineation of nuclei. To address these challenges, a technique called structured illumination microscopy (SIM) was employed in which the entire FOV is illuminated with a defined spatial pattern rather than scanning a focal spot, such as in confocal microscopy.

Thus, the second aim was to improve image contrast and increase the FOV through employing wide-field, non-contact structured illumination microscopy and optimize the segmentation algorithm for new imaging modality. Both image contrast and FOV were increased through the development of a wide-field fluorescence SIM system. Clear improvement in image contrast was seen in structured illumination images compared to uniform illumination images. Additionally, the FOV is over 13X larger than the fluorescence microendoscope used in aim 1. Initial segmentation results of SIM images revealed that SCA is unable to segment large numbers of APFs in the tumor images. Because the FOV of the SIM system is over 13X larger than the FOV of the fluorescence microendoscope, dense collections of APFs commonly seen in tumor images could no longer be sparsely represented, and the fundamental sparsity assumption associated with SCA was no longer met. Thus, an algorithm called maximally stable extremal regions (MSER) was investigated as an alternative approach for APF segmentation in SIM images. MSER was able to accurately segment large numbers of APFs in SIM images of tumor tissue. In addition to optimizing MSER for SIM image segmentation, an optimal frequency of the illumination pattern used in SIM was carefully selected because the image signal to noise ratio (SNR) is dependent on the grid frequency. A grid frequency of 31.7 mm-1 led to the highest SNR and lowest percent error associated with MSER segmentation.

Once MSER was optimized for SIM image segmentation and the optimal grid frequency was selected, a quantitative model was developed to diagnose mouse sarcoma tumor margins that were imaged ex vivo with SIM. Tumor margins were stained with acridine orange (AO) in aim 2 because AO was found to stain the sarcoma tissue more brightly than acriflavine. Both acriflavine and AO are intravital dyes, which have been shown to stain nuclei, skeletal muscle, and collagenous stroma. A tissue-type classification model was developed to differentiate localized regions (75x75 µm) of tumor from skeletal muscle and adipose tissue based on the MSER segmentation output. Specifically, a logistic regression model was used to classify each localized region. The logistic regression model yielded an output in terms of probability (0-100%) that tumor was located within each 75x75 µm region. The model performance was tested using a receiver operator characteristic (ROC) curve analysis that revealed 77% sensitivity and 81% specificity. For margin classification, the whole margin image was divided into localized regions and this tissue-type classification model was applied. In a subset of 6 margins (3 negative, 3 positive), it was shown that with a tumor probability threshold of 50%, 8% of all regions from negative margins exceeded this threshold, while over 17% of all regions exceeded the threshold in the positive margins. Thus, 8% of regions in negative margins were considered false positives. These false positive regions are likely due to the high density of APFs present in normal tissues, which clearly demonstrates a challenge in implementing this automatic algorithm based on AO staining alone.

Thus, the third aim was to improve the specificity of the diagnostic model through leveraging other sources of contrast. Modifications were made to the SIM system to enable fluorescence imaging at a variety of wavelengths. Specifically, the SIM system was modified to enabling imaging of red fluorescent protein (RFP) expressing sarcomas, which were used to delineate the location of tumor cells within each image. Initial analysis of AO stained panels confirmed that there was room for improvement in tumor detection, particularly in regards to false positive regions that were negative for RFP. One approach for improving the specificity of the diagnostic model was to investigate using a fluorophore that was more specific to staining tumor. Specifically, tetracycline was selected because it appeared to specifically stain freshly excised tumor tissue in a matter of minutes, and was non-toxic and stable in solution. Results indicated that tetracycline staining has promise for increasing the specificity of tumor detection in SIM images of a preclinical sarcoma model and further investigation is warranted.

In conclusion, this work presents the development of a combination of tools that is capable of automated segmentation and quantification of micro-anatomical images of thick tissue. When compared to the fluorescence microendoscope, wide-field multispectral fluorescence SIM imaging provided improved image contrast, a larger FOV with comparable resolution, and the ability to image a variety of fluorophores. MSER was an appropriate and rapid approach to segment dense collections of APFs from wide-field SIM images. Variables that reflect the morphology of the tissue, such as the density, size, and shape of nuclei and nucleoli, can be used to automatically diagnose SIM images. The clinical utility of SIM imaging and MSER segmentation to detect microscopic residual disease has been demonstrated by imaging excised preclinical sarcoma margins. Ultimately, this work demonstrates that fluorescence imaging of tissue micro-anatomy combined with a specialized algorithm for delineation and quantification of features is a means for rapid, non-destructive and automated detection of microscopic disease, which could improve cancer management in a variety of clinical scenarios.

Structured Illumination Microscopy and a Quantitative Image Analysis for the Detection of Positive Margins in a Pre-Clinical Genetically Engineered Mouse Model of Sarcoma.

Intraoperative assessment of surgical margins is critical to ensuring residual tumor does not remain in a patient. Previously, we developed a fluorescence structured illumination microscope (SIM) system with a single-shot field of view (FOV) of 2.1 × 1.6 mm (3.4 mm2) and sub-cellular resolution (4.4 μm). The goal of this study was to test the utility of this technology for the detection of residual disease in a genetically engineered mouse model of sarcoma. Primary soft tissue sarcomas were generated in the hindlimb and after the tumor was surgically removed, the relevant margin was stained with acridine orange (AO), a vital stain that brightly stains cell nuclei and fibrous tissues. The tissues were imaged with the SIM system with the primary goal of visualizing fluorescent features from tumor nuclei. Given the heterogeneity of the background tissue (presence of adipose tissue and muscle), an algorithm known as maximally stable extremal regions (MSER) was optimized and applied to the images to specifically segment nuclear features. A logistic regression model was used to classify a tissue site as positive or negative by calculating area fraction and shape of the segmented features that were present and the resulting receiver operator curve (ROC) was generated by varying the probability threshold. Based on the ROC curves, the model was able to classify tumor and normal tissue with 77% sensitivity and 81% specificity (Youden's index). For an unbiased measure of the model performance, it was applied to a separate validation dataset that resulted in 73% sensitivity and 80% specificity. When this approach was applied to representative whole margins, for a tumor probability threshold of 50%, only 1.2% of all regions from the negative margin exceeded this threshold, while over 14.8% of all regions from the positive margin exceeded this threshold.

Characterization of the FKBP12-Encoding Genes in Aspergillus fumigatus.

Invasive aspergillosis, largely caused by Aspergillus fumigatus, is responsible for a growing number of deaths among immunosuppressed patients. Immunosuppressants such as FK506 (tacrolimus) that target calcineurin have shown promise for antifungal drug development. FK506-binding proteins (FKBPs) form a complex with calcineurin in the presence of FK506 (FKBP12-FK506) and inhibit calcineurin activity. Research on FKBPs in fungi is limited, and none of the FKBPs have been previously characterized in A. fumigatus. We identified four orthologous genes of FKBP12, the human FK506 binding partner, in A. fumigatus and designated them fkbp12-1, fkbp12-2, fkbp12-3, and fkbp12-4. Deletional analysis of the four genes revealed that the Δfkbp12-1 strain was resistant to FK506, indicating FKBP12-1 as the key mediator of FK506-binding to calcineurin. The endogenously expressed FKBP12-1-EGFP fusion protein localized to the cytoplasm and nuclei under normal growth conditions but also to the hyphal septa following FK506 treatment, revealing its interaction with calcineurin. The FKBP12-1-EGFP fusion protein didn't localize at the septa in the presence of FK506 in the cnaA deletion background, confirming its interaction with calcineurin. Testing of all deletion strains in the Galleria mellonella model of aspergillosis suggested that these proteins don't play an important role in virulence. While the Δfkbp12-2 and Δfkbp12-3 strains didn't show any discernable phenotype, the Δfkbp12-4 strain displayed slight growth defect under normal growth conditions and inhibition of the caspofungin-mediated "paradoxical growth effect" at higher concentrations of the antifungal caspofungin. Together, these results indicate that while only FKBP12-1 is the bona fide binding partner of FK506, leading to the inhibition of calcineurin in A. fumigatus, FKBP12-4 may play a role in basal growth and the caspofungin-mediated paradoxical growth response. Exploitation of differences between A. fumigatus FKBP12-1 and human FKBP12 will be critical for the generation of fungal-specific FK506 analogs to inhibit fungal calcineurin and treat invasive fungal disease.

Differential developmental trajectories of magnetic susceptibility in human brain gray and white matter over the lifespan

As indicated by several recent studies, magnetic susceptibility of the brain is influenced mainly by myelin in the white matter and by iron deposits in the deep nuclei. Myelination and iron deposition in the brain evolve both spatially and temporally. This evolution reflects an important characteristic of normal brain development and ageing. In this study, we assessed the changes of regional susceptibility in the human brain in vivo by examining the developmental and ageing process from 1 to 83 years of age. The evolution of magnetic susceptibility over this lifespan was found to display differential trajectories between the gray and the white matter. In both cortical and subcortical white matter, an initial decrease followed by a subsequent increase in magnetic susceptibility was observed, which could be fitted by a Poisson curve. In the gray matter, including the cortical gray matter and the iron-rich deep nuclei, magnetic susceptibility displayed a monotonic increase that can be described by an exponential growth. The rate of change varied according to functional and anatomical regions of the brain. For the brain nuclei, the age-related changes of susceptibility were in good agreement with the findings from R2* measurement. Our results suggest that magnetic susceptibility may provide valuable information regarding the spatial and temporal patterns of brain myelination and iron deposition during brain maturation and ageing. © 2013 Wiley Periodicals, Inc.

Towards more accurate and reliable predictions for nuclear applications

The need for nuclear data far from the valley of stability, for applications such as nuclear as- trophysics or future nuclear facilities, challenges the robustness as well as the predictive power of present nuclear models. Most of the nuclear data evaluation and prediction are still performed on the basis of phenomenological nuclear models. For the last decades, important progress has been achieved in funda- mental nuclear physics, making it now feasible to use more reliable, but also more complex microscopic or semi-microscopic models in the evaluation and prediction of nuclear data for practical applications. In the present contribution, the reliability and accuracy of recent nuclear theories are discussed for most of the relevant quantities needed to estimate reaction cross sections and beta-decay rates, namely nuclear masses, nuclear level densities, gamma-ray strength, fission properties and beta-strength functions. It is shown that nowadays, mean-field models can be tuned at the same level of accuracy as the phenomenological mod- els, renormalized on experimental data if needed, and therefore can replace the phenomenogical inputs in the prediction of nuclear data. While fundamental nuclear physicists keep on improving state-of-the-art models, e.g. within the shell model or ab initio models, nuclear applications could make use of their most recent results as quantitative constraints or guides to improve the predictions in energy or mass domain that will remain inaccessible experimentally.

Effects Of Aromatic-Hydrocarbons On The Metabolism Of The Digestive Gland Of The Mussel Mytilus-Edulis-L

1. The results presented in this paper show that the exposure of mussels to a sublethal concentration of oil-derived aromatic hydrocarbons (30 μg 1−1) for a period of 4 months significantly decreases the protein level in the digestive gland of the animals (−17%). 2. The activity of the nuclear RNA polymerase I and II is also significantly decreased in the digestive gland of hydrocarbon-exposed mussels (−64% and −18%, respectively). 3. The RNAase(s) activity present in the nuclei from the digestive gland cells increases following the exposure of the mussels to aromatic hydrocarbons. This effect is particularly evident at high ionic strength [200 mM (NH4)2SO4]. 4. The analysis of some characteristics of the nuclear RNAase(s) (most of which is soluble and shows a maximum of activity at pH 4−5) could indicate that part of this hydrolytic enzyme may have a lysosomal origin. 5. This fact appears to be in agreement with the finding that in the mussels exposed for 4 months to aromatic hydrocarbons the lysosomal stability decreases drastically and the total content of lysosomal enzymes is significantly increased (+42.4%).

Ocean acidification has different effects on the production of DMS and DMSP measured in cultures of Emiliania huxleyi and a mesocosm study: a comparison of laboratory monocultures and community interactions

The human-induced rise in atmospheric carbon dioxide since the industrial revolution has led to increasing oceanic carbon uptake and changes in seawater carbonate chemistry, resulting in lowering of surface water pH. In this study we investigated the effect of increasing CO2 partial pressure (pCO2) on concentrations of volatile biogenic dimethylsulfide (DMS) and its precursor dimethylsulfoniopropionate (DMSP), through monoculture studies and community pCO2 perturbation. DMS is a climatically important gas produced by many marine algae: it transfers sulfur into the atmosphere and is a major influence on biogeochemical climate regulation through breakdown to sulfate and formation of subsequent cloud condensation nuclei (CCN). Overall, production of DMS and DMSP by the coccolithophore Emiliania huxleyi strain RCC1229 was unaffected by growth at 900 matm pCO2, but DMSP production normalised to cell volume was 12% lower at the higher pCO2 treatment. These cultures were compared with community DMS and DMSP production during an elevated pCO2 mesocosm experiment with the aim of studying E. huxleyi in the natural environment. Results contrasted with the culture experiments and showed reductions in community DMS and DMSP concentrations of up to 60 and 32% respectively at pCO2 up to 3000 matm, with changes attributed to poorer growth of DMSP-producing nanophytoplankton species, including E. huxleyi, and potentially increased microbial consumption of DMSand dissolvedDMSPat higher pCO2.DMSandDMSPproduction differences between culture and community likely arise from pH affecting the inter-species responses between microbial producers and consumers.

Identidad territorial y paisaje. Evolución morfológica de los núcleos en Castilla y León.

Este estudio intenta esclarecer las transformaciones físicas y socioeconómicas de los asentamientos rurales de la región española de Castilla y León, durante la segunda mitad del siglo XX. Se analiza la evolución temporal de la forma urbana a través de un Sistema de Información Geográfico (SIG), calculando unos índices métricos y comparándolos con la información demográfica histórica. Los resultados pretenden mostrar los efectos de la especialización funcional económica, causada por la integración en las jerarquías productivas globales, sobre la estructura urbana. La pérdida gradual de las características tradicionales de los pueblos castellanos, como la compacidad y la integración en el entorno, debido a la pérdida o degradación de la arquitectura popular y la construcción de nuevas edificaciones industriales, supone un riesgo para las futuras políticas de desarrollo local. Se considera necesario preservar la identidad paisajística y evitar la destrucción del patrimonio cultural para poder revitalizar estos territorios.